Deep investigation of an incident or finding. Performs thorough root cause analysis with hypothesis testing and evidence gathering. Use after /incident or /finding.
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name
investigate
description
Deep investigation of an incident or finding. Performs thorough root cause analysis with hypothesis testing and evidence gathering. Use after /incident or /finding.
context
fork
agent
general-purpose
disable-model-invocation
false
argument-hint
[finding-ref or description]
effort
xhigh
wrought
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Deep Investigation Skill
Routing note (Pass-A): This skill runs as a forked general-purpose agent (context: fork). Forking sub-steps spawn with an explicit model+effort per the Pass-A default (floor high, default xhigh for coding/agentic sub-steps); max is reserved for Pass-B-gated escalations (e.g. loop-stall, irreversible-tag) — it is not the default for every spawn. See docs/reference/dynamic_stage_routing_policy.md.
Trigger: Use /investigate {incident or finding report} when you need a thorough investigation of an incident, bug, unexpected behavior, or proactive finding.
Input: An incident report (from /incident) or a finding report (from /finding) describing what happened or what was found.
Examples:
/investigate Extraction hung at 12% - no error in logs, last event was url_refresh_triggered at 07:38 UTC
/investigate Rate limiting errors despite batch processing - 429 responses every 2 seconds starting 14:00 UTC
/investigate Health check showing red but API responding - monitor page shows Backend=red since 09:15 UTC
/investigate Finding: Missing companyId filter in invoice WHERE clauses -- authorization gap
Prerequisites
Before executing this skill, verify ALL of the following:
Use Glob to check for: docs/findings/*_FINDINGS_TRACKER.md or docs/incidents/*.md
If NO match -> STOP: "Run /finding or /incident first to create an upstream artifact."
If user says --force, proceed without validation.
Read the most recent Findings Tracker matching *_FINDINGS_TRACKER.md
Identify the relevant finding (ask user if ambiguous)
Pre-flight Check
Verify artifact prerequisites (above)
Identify which finding/workflow this is for
Load finding report and related artifacts for context
Proceed to main skill instructions
Instructions
Reason thoroughly about this incident or finding. Consider all evidence, form multiple hypotheses, and test each systematically before concluding.
Input Type Detection
Determine the input type and route accordingly:
IF input references a finding report (docs/findings/*.md) OR starts with "Finding:":
→ Confirmation Mode (abbreviated investigation)
ELSE:
→ Full Investigation Mode (standard investigation)
Full Investigation Mode (incidents)
Research online for relevant documentation and known issues (search as of {current_month_year})
Consult relevant API/library documentation based on what the incident involves (search as of {current_month_year})
Deeply investigate the incident provided after /investigate
Review past RCAs and Investigations in docs/RCAs/ and docs/investigations/ to avoid repeating errors and recognize patterns
Write detailed Investigation Report to docs/investigations/{YYYY-MM-DD_HHMM}_{issue_name}.md
THEN STOP and await further instructions
Optional — supervised Fable hypothesis-generator (baffling exhausted root cause only): if the root cause stays open after a thorough Full Investigation, the operator may manually spawn ONE Claude Fable 5 hypothesis-generator via the Agent tool — it generates candidate hypotheses only, never a verdict. Test each candidate on the Opus session model; watch for refused/empty output (a refusal is a non-answer, not a clean bill); the human reads the RCA before /rca-bugfix. Manual, opt-in, owner/ZDR-free only — no committed model: pin (see CST-004).
Confirmation Mode (findings)
When a proactive finding is provided, the cause is often already known. The investigation confirms scope and validates the finding:
Read the finding report in docs/findings/ to understand what was found
Confirm the finding is real -- reproduce or verify the evidence
Determine scope -- is it isolated or systemic?
Document additional evidence beyond what the finding captured
Assess impact -- what is the blast radius if unaddressed?
Write abbreviated Investigation Report to docs/investigations/{YYYY-MM-DD_HHMM}_{issue_name}.md
THEN STOP and await further instructions
Investigation Process
Step 1: External Research
Search online (use current date context: {current_month_year}):
Search for known issues, bugs, or limitations related to the problem
Search for relevant API documentation updates
Look for community discussions or Stack Overflow answers
Consult Relevant Documentation:
First, identify what technology/API/library the incident involves. Then search for documentation specific to that technology.
EXAMPLES (use these as a pattern, NOT as default searches):
If the incident involves Stripe: Search "Stripe API {relevant_topic} {current_month_year}"
If the incident involves Slack: Search "Slack API {relevant_topic} {current_month_year}"
If the incident involves GCS/Google Cloud Storage: Search "Google Cloud Storage {relevant_topic} {current_month_year}"
If the incident involves httpx/requests: Search "Python httpx {relevant_topic} {current_month_year}"
If the incident involves FastAPI: Search "FastAPI {relevant_topic} {current_month_year}"
If the incident involves PostgreSQL: Search "PostgreSQL {relevant_topic} {current_month_year}"
IMPORTANT: Only search documentation relevant to the actual incident. Do NOT default to searching Stripe or Slack docs unless the incident specifically involves those APIs.
From the documentation, extract:
Rate limits, timeouts, expected behavior
Recent API changes or deprecations
Known limitations or gotchas
Step 2: Gather Internal Evidence
Search logs for relevant events
Read related source code files
Check recent changes that might be related
Look for patterns in timing, data, or behavior
Step 3: Build Timeline
Construct a precise timeline of events:
When did the incident first appear?
What happened immediately before?
What was the system state?
Step 4: Identify Root Cause
Distinguish between symptoms and causes
Identify primary, secondary, and contributing factors
Trace the code path that led to the incident
Compare our implementation against official API documentation
Step 5: Analyze Impact
What was affected?
How much data/time was lost?
What is the blast radius?
Step 6: Review Past RCAs and Investigations (MANDATORY)
Before recommending any fixes, read all files in: docs/RCAs/, docs/research/, docs/plans/, docs/investigations/, docs/findings/. Look for similar issues, prior fixes, recurring patterns, and applicable solutions.
Document patterns found: Has this exact or similar issue occurred before? Did a previous fix cause this? Is this a regression?
Write to: docs/investigations/{YYYY-MM-DD_HHMM}_{issue_name}.md
After Writing the Report
Full Investigation Mode Output
STOP and tell the user:
Investigation complete.
Report saved to: docs/investigations/{YYYY-MM-DD_HHMM}_{issue_name}.md
Summary: {1-2 sentence summary}
Sources consulted:
- {List of documentation/URLs researched}
Past RCAs/Investigations/Research reviewed:
- {List of related past documents consulted}
**CRITICAL PIPELINE RULE**: Suggest ONLY the next pipeline step below. Do NOT offer `/plan` directly — that comes after `/rca-bugfix`.
Next step: Run `/rca-bugfix` with the investigation at `docs/investigations/{filename}.md` to create RCA and implementation prompt.
Do NOT add commentary suggesting any pipeline step could be skipped or is unnecessary. Awaiting your instructions.
Confirmation Mode Output
STOP and tell the user:
Finding confirmed.
Report saved to: docs/investigations/{YYYY-MM-DD_HHMM}_{issue_name}.md
Finding: {reference to original finding report}
Scope: {isolated | systemic | broader than expected}
Confirmed: {Yes -- real issue | Partially -- narrower than reported | No -- false positive}
**CRITICAL PIPELINE RULE**: Suggest ONLY the next pipeline step below. Do NOT offer `/plan` directly — that comes after `/rca-bugfix`.
Next step: Run `/rca-bugfix` with the investigation at `docs/investigations/{filename}.md` to create RCA and fix prompt.
Do NOT add commentary suggesting any pipeline step could be skipped or is unnecessary. Awaiting your instructions.
Do NOT proceed with fixes or additional work until the user responds.
